Revision as of 08:09, 26 June 2013

Purpose

The purpose of this tutorial/workshop session will be to give an introduction to using the Hall-D analysis tools. It is open to anyone either inside or outside the GlueX collaboration who has an interest in doing physics inside Hall-D. The tutorial will cover the basics of:

• Physics Analysis Framework
• Using Boosted Decision Trees
• Amplitude Analysis using AMPtools

The tutorial will consist of a few talks with room for questions/discussion.

Location and Time

The tutorial will take place:

DATE: July. 10-11, 2013

TIME: 9:00am to 4:30pm EDT (i.e. JLab time).

LOCATION: CEBAF Center L102 - L104

Registration

Registration Page

Remote Participation

To connect from the outside by phone please do the following

1.) ESNET: 8542553

2.) Polycom RealPrescence App for iOS and Android. Call 8542553@gk1.es.net

3.) Telephone:

Dial +1-866-740-1260 : US and Canada

Dial +1-303-248-0285 : International

Then use participant code: 3421244# (the # is needed when using the phone) or www.readytalk.com then type access code 3421244 into "join a meeting" (you need java plugin)

4.) As of January 1, 2013 EVO became SeeVogh and Jefferson Lab has a contract to use it.

   To connect via SeeVogh, vist their website at research.seevogh.com. Your old EVO credentials are supposed to work. There will be a room booked for the meeting.
   To phone into an EVO meeting, from the U.S. call (626) 395-2112 and then enter the EVO meeting code. Instructions for the Phone Bridge to EVO.
   Skype Bridge to EVO 

5.) Please visit the Communications page for some options.

Schedule Details (Work in Progress)

Overview (Matt)

• Talk (30 min): Physics Overview and Analysis Strategy
  • Define the physics goals
  • Discuss detector
  • Discuss general analysis strategy
• Talk (15 min): A specific physics example: γp→π⁺π⁺π^-n
• Exercise (15 min): Generate γp→π⁺π⁺π^-n with intermediate resonances

Monte Carlo Generators and Detector Simulation (Mark)

• Talk (30 min): Other standard monte carlo tools (bggen, genr8, hdgeant, mcsmear)
• Exercise (20 min): Generate pythia data, run HDGeant and mcsmear

JANA/DANA (Paul)

• Talk (35 mins): Intro to JANA/DANA (factories & plugins)
  • JANA is a framework: multithreaded, factory-based (describe concept of factories, tags (e.g. BCAL)), event-processors control the work flow
  • The primary executable (hd_root) does virtually nothing by itself, the processor in your plugin tells it what to do
  • JANA automatically loops over the events in your input files, executing the primary factory & plugin methods as needed: init(), brun(), evnt(), erun(), fini()
  • Track/Shower reconstruction, REST format, danarest plugin
  • Basic Analysis Classes: DKinematicData, DChargedTrackHypothesis, DChargedTrack, DNeutralShower, DMCThrown, DBeamPhoton
  • hd_dump: Prints data to screen
• Exercise (25 mins):
  • Use danarest plugin to do track reconstruction.
  • Print basic analysis objects (DMCThrown, etc.) to screen via hd_dump and inside of plugin
  • Stretch goal: figure out how to get the run number from inside the evnt() method and print it to screen for each event.

ANALYSIS Library (Paul)

Analysis Basics

• Talk (25 mins):
  • User specifies reaction & decay chain, library generates all particle combinations
  • Particle Combinations: Why, and why so many? (extra tracks, any PID of same q, decay products of different particles, beware double-counting), DParticleCombo contents
  • Basic example plugin: 3pi_n (go over line by line)
• Exercise (25 mins):
  • Generate 3pi_n plugin, manually histogram: #combos, #events with >= 1 combo, missing mass (calc manually), p-vs-theta & vertex-z for pi+'s and pi-'s

Kinematic Fitting

• Talk (30 mins):
  • What it is, how it works, constraints, how neutrals & magnetic field are handled
  • Setting it up automatically and manually (go over line-by-line)
• Exercise (30 mins):
  • Auto-kinematic fit 3pi_n, histogram kinematic fit confidence level, missing mass after kinematic fit (conlev > 1%)
  • Manually kinematic fit 3pi_n, including histograming confidence levels, missing mass after kinematic fit (conlev > 1%)
  • Stretch goal: histogram pi- px and vx pulls (conlev > 5%)

Analysis Details

• Talk (30 mins):
  • Thrown/Reconstructed track matching, PID FOM Calculation, new DTrackTimeBased for new PIDs (q+/q- subtlety), Event RF Bunch Selection
  • Different object versions (DParticleCombo, hypotheses)
• Exercise (25 mins):
  • Manually histogram: pid conlevs (dE/dx, timing, total)
  • Stretch goal: histogram pid confidence level vs. projected track start time for different PIDs for BCAL/TOF

Analysis Actions - Pre-existing

• Talk (25 mins):
  • Reaction-Independent (can be called manually): thrown, reconstructed track distros, gen-recon comparison (go over line-by-line on one)
  • Reaction-Dependent Histograms (executed for each combo): PID, kinfit results, missing mass, invariant mass (go over line-by-line on one)
  • Reaction-Dependent Cuts (executed for each combo): PID, kinfit conlev, missing mass, invariant mass (go over line-by-line on one)
  • #events/combos pass cuts histograms
• Exercise (25 mins):
  • Add reaction-independent analysis actions: fill histograms and look at kinematics in ROOT
  • Add reaction-dependent analysis actions: hist/cut pid, hist/cut kinematic fit results, hist missing mass before/after kinfit conlev cut

Analysis Actions - Custom

• Talk (10 mins):
  • Creating your own custom actions, remind to beware double-counting, warn about multi-threading issues
• Exercise (15 mins):
  • Generate custom action to make dalitz plot of 3 pions.

REST & ROOT

• Talk (25 mins):
  • REST Skims, TTree format, Making/Using a TSelector, beware double-counting when filling ROOT trees.
• Exercise (30 mins):
  • Create a skim of 3pi_n events, analyze the skim data, save the results to a root ttree, analyze the data in ROOT (make some plots)

Analyzing Decays

• Talk (5 mins):
  • Setting up DReaction
• Exercise (45 mins):
  • Make a plugin to analyze: γp→η'p, η'→ηπ⁺π^-, η→γγ
    • Do kinematic fitting, output to ROOT, histogram PID, kinfitresults, mass peaks, etc.

Boosted Decision Trees (Mike & Justin)

• Talk (45 mins): Multivariate Analysis Overview
• Talk (20 mins):
  • Introduce TMVA, setup factory, select input variables, book methods, and training samples
• Exercise (25 mins):
  • Train BDT using 3pi_n samples, make plots of input variables and classifier response with TMVAGui
• Talk (20 mins):
  • Describe weight files, setup reader, evaluation on larger samples, and storing classifier response in TTree
• Exercise (25 mins):
  • Apply BDT to large background sample, compute efficiency and purity
• Talk (10 mins):
  • Describe setup for other Multivariate Classifiers
• Exercise (20 mins):
  • Try many different classifiers for 3pi_n channel and evaluate with TMVAGui

Amplitude Analysis (Matt)

• Talk (45 mins): Amplitude Analysis Fitting Strategy
• Exercise (20 mins): performing a single fit and analyzing projections
• Talk (30 mins): Multiple fits, opportunities for extensions
• Exercise (20 mins): performing multiple fits in different bins of a mass spectrum